Opening the door on entry inhibitors in HIV: Redefining the use of entry inhibitors in heavily treatment experienced and treatment‐limited individuals living with HIV
Bibliographic record
Abstract
INTRODUCTION: Entry inhibitors are a relatively new class of antiretroviral therapy and are typically indicated in heavily treatment experienced individuals living with HIV. Despite this, there is no formal definition of 'heavily treatment experienced'. Interpretation of this term generally includes acknowledgement of multidrug resistance and reflects the fact that patients in need of further treatment options may have experienced multiple lines of therapy. However, it fails to recognize treatment limiting factors including contraindications, age-associated comorbidities, and difficulty adhering to regimens. METHODS: This manuscript follows a roundtable discussion and aims to identify the unmet needs of those living with HIV who are in need of further treatment options, to broaden the definition of heavily treatment experienced and to clarify the use of newer agents, with an emphasis on the potential role of entry inhibitors, in this population. RESULTS/CONCLUSIONS: Within the entry inhibitor class, mechanisms of action differ between agents; resistance to one subclass does not confer resistance to others. Combinations of entry inhibitors should be considered in the same regimen, and if lack of response is seen to one entry inhibitor another can be tried. When selecting an entry inhibitor, physicians should account for patient preferences and needs as well as agent-specific clinical characteristics. Absence of documented multidrug resistance should not exclude an individual from treatment with an entry inhibitor; entry inhibitors are a valuable treatment option for all individuals who are treatment limited or treatment exhausted. We should advocate for additional clinical trials that help define the role of entry inhibitors in people with exhausted/limited ART options other than drug resistance.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.012 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".